Systematic analysis of multi-omics data reveals component-specific blood-based biomarkers for Parkinson’s disease

Abstract

Parkinson’s disease (PD) is a prevalent neurodegenerative disorder affecting millions of elderly individuals worldwide. Clinically, PD is diagnosed based on the presentation of motoric symptoms. Other methods such as F-DOPA PET scan or α-Synuclein detection from the cerebral spinal fluid are either too expensive or invasive for routine use. Omics platforms such as transcriptomics, proteomics, and metabolomics may identify PD biomarkers from blood, which can reduce cost and increase efficiency. However, there are many biological moieties being measured and issues with false positives/negatives. It is also unknown which omics platform offers most useful information. Therefore, it is important to assess the reliability of these omics studies. Here, we shortlisted and analysed nearly 80 published reports across transcriptomics, proteomics and metabolomics in search of overlapping blood-based biomarkers for PD. The top biomarkers were reported across 29%, 42% and 12.5% of shortlisted papers in transcriptomics, proteomics and metabolomics respectively. These percentages increased to 42%, 60% and 50% accordingly when studies were grouped by specific blood subtypes for analysis, demonstrating the need for test kits to be blood-subtype specific. Following systematic analyses, we propose six novel PD biomarkers: two mRNAs (Whole blood, WB) – Arg1 and SNCA, two proteins (Plasma EV) – SNCA and APOA1, and two metabolites (WB) – 8-OHdG and uric acid for further validation. While these proposed biomarkers are useful, they are also snapshots, representing subsets of larger pathways of origin where the different omics levels corroborate. Indeed, identifying the interconnections across different biological layers can strengthen contextual reasoning, which in turn, would give rise to better quality biomarkers. Knowledge integration across the omics spectrum revealed consistent aberrations on the same neuroinflammation pathway, showcasing the value of integrative (i)-omics agreements for increasing confidence of biomarker selection. We believe that our findings could pave the way for identifying reproducible PD biomarkers, with potential for clinical deployment.Graphical Six Proposed blood-based biomarkers. Seventy-nine publications across transcriptomics, proteomics and metabolomics were shortlisted and analysed for reported biomarkers. The proposed biomarkers are SNCA, APOA1, Arg1, 8-OHdG and Uric acid.